"Dual-scale correlation analysis for robust multi-label classification" by Kaixiang Wang, Ming Yang et al.
Noise in label space is a major challenge in the multi-label classification problem, as the noise (including false-negative noise and false-positive noise) can affect the distribution of the label space, which causes serious interference to the performance of the learned model. Existing methods have initially solved the situation where false-negative noise and false-positive noise appear separately, but classification when the two kinds of noise appear at the same time is still a challenging problem that has not yet been solved. This paper proposed a novel method named Dual-Scale Correlation A...
Source: uow.edu.au